Overview

Dataset statistics

Number of variables17
Number of observations9838
Missing cells18974
Missing cells (%)11.3%
Duplicate rows1
Duplicate rows (%)< 0.1%
Total size in memory1.4 MiB
Average record size in memory144.0 B

Variable types

Text2
Numeric15

Alerts

Dataset has 1 (< 0.1%) duplicate rowsDuplicates
Murder is highly overall correlated with Rape and 3 other fieldsHigh correlation
Rape is highly overall correlated with Murder and 4 other fieldsHigh correlation
Kidnapping and Abduction is highly overall correlated with Murder and 4 other fieldsHigh correlation
Other Crimes is highly overall correlated with Murder and 3 other fieldsHigh correlation
Total is highly overall correlated with Murder and 4 other fieldsHigh correlation
Other murder is highly overall correlated with Rape and 2 other fieldsHigh correlation
Murder has 834 (8.5%) missing valuesMissing
Infanticid has 9015 (91.6%) missing valuesMissing
Other murder has 9015 (91.6%) missing valuesMissing
Kidnapping and Abduction is highly skewed (Îł1 = 22.69153087)Skewed
Abetment of suicide is highly skewed (Îł1 = 34.85889673)Skewed
Procuration of minor girls is highly skewed (Îł1 = 25.54403979)Skewed
Buying of girls for prostitution is highly skewed (Îł1 = 25.40693801)Skewed
Selling of girls for prostitution is highly skewed (Îł1 = 29.18916002)Skewed
Murder has 4491 (45.6%) zerosZeros
Rape has 3927 (39.9%) zerosZeros
Kidnapping and Abduction has 4250 (43.2%) zerosZeros
Foeticide has 9014 (91.6%) zerosZeros
Abetment of suicide has 9319 (94.7%) zerosZeros
Exposure and abandonment has 7673 (78.0%) zerosZeros
Procuration of minor girls has 9013 (91.6%) zerosZeros
Buying of girls for prostitution has 9705 (98.6%) zerosZeros
Selling of girls for prostitution has 9545 (97.0%) zerosZeros
Prohibition of child marriage act has 8857 (90.0%) zerosZeros
Other Crimes has 5883 (59.8%) zerosZeros
Total has 2692 (27.4%) zerosZeros
Infanticid has 760 (7.7%) zerosZeros
Other murder has 360 (3.7%) zerosZeros

Reproduction

Analysis started2023-09-14 17:28:36.801294
Analysis finished2023-09-14 17:31:08.867321
Duration2 minutes and 32.07 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

Distinct70
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:10.591204image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length17
Median length13
Mean length9.8077861
Min length3

Characters and Unicode

Total characters96489
Distinct characters48
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowANDHRA PRADESH
2nd rowANDHRA PRADESH
3rd rowANDHRA PRADESH
4th rowANDHRA PRADESH
5th rowANDHRA PRADESH
ValueCountFrequency (%)
pradesh 2448
 
17.3%
uttar 955
 
6.8%
madhya 683
 
4.8%
maharashtra 598
 
4.2%
bihar 584
 
4.1%
tamil 509
 
3.6%
nadu 509
 
3.6%
rajasthan 498
 
3.5%
odisha 467
 
3.3%
452
 
3.2%
Other values (37) 6420
45.5%
2023-09-14T23:01:12.213913image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 20212
20.9%
H 8945
 
9.3%
R 8635
 
8.9%
S 5462
 
5.7%
T 5325
 
5.5%
D 5184
 
5.4%
4285
 
4.4%
N 3875
 
4.0%
M 3820
 
4.0%
E 3480
 
3.6%
Other values (38) 27266
28.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 85211
88.3%
Lowercase Letter 6535
 
6.8%
Space Separator 4285
 
4.4%
Other Punctuation 458
 
0.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 20212
23.7%
H 8945
10.5%
R 8635
10.1%
S 5462
 
6.4%
T 5325
 
6.2%
D 5184
 
6.1%
N 3875
 
4.5%
M 3820
 
4.5%
E 3480
 
4.1%
U 3130
 
3.7%
Other values (13) 17143
20.1%
Lowercase Letter
ValueCountFrequency (%)
a 1737
26.6%
h 769
11.8%
r 736
11.3%
s 496
 
7.6%
d 431
 
6.6%
t 431
 
6.6%
e 322
 
4.9%
n 290
 
4.4%
i 266
 
4.1%
m 202
 
3.1%
Other values (13) 855
13.1%
Space Separator
ValueCountFrequency (%)
4285
100.0%
Other Punctuation
ValueCountFrequency (%)
& 458
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 91746
95.1%
Common 4743
 
4.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 20212
22.0%
H 8945
 
9.7%
R 8635
 
9.4%
S 5462
 
6.0%
T 5325
 
5.8%
D 5184
 
5.7%
N 3875
 
4.2%
M 3820
 
4.2%
E 3480
 
3.8%
U 3130
 
3.4%
Other values (36) 23678
25.8%
Common
ValueCountFrequency (%)
4285
90.3%
& 458
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 96489
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 20212
20.9%
H 8945
 
9.3%
R 8635
 
8.9%
S 5462
 
5.7%
T 5325
 
5.5%
D 5184
 
5.4%
4285
 
4.4%
N 3875
 
4.0%
M 3820
 
4.0%
E 3480
 
3.6%
Other values (38) 27266
28.3%
Distinct840
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:13.661625image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length20
Median length17
Mean length8.3778207
Min length3

Characters and Unicode

Total characters82421
Distinct characters38
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)0.4%

Sample

1st rowADILABAD
2nd rowANANTAPUR
3rd rowCHITTOOR
4th rowCUDDAPAH
5th rowEAST GODAVARI
ValueCountFrequency (%)
total 454
 
3.8%
rural 340
 
2.9%
commr 229
 
1.9%
rly 221
 
1.9%
west 120
 
1.0%
g.r.p 115
 
1.0%
east 111
 
0.9%
nagar 98
 
0.8%
south 91
 
0.8%
north 91
 
0.8%
Other values (766) 9935
84.2%
2023-09-14T23:01:15.777725image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 15576
18.9%
R 8428
 
10.2%
I 4680
 
5.7%
N 4643
 
5.6%
H 4600
 
5.6%
U 4485
 
5.4%
L 3870
 
4.7%
T 3681
 
4.5%
O 3225
 
3.9%
D 3095
 
3.8%
Other values (28) 26138
31.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 79145
96.0%
Space Separator 1967
 
2.4%
Other Punctuation 1020
 
1.2%
Dash Punctuation 84
 
0.1%
Open Punctuation 56
 
0.1%
Close Punctuation 56
 
0.1%
Decimal Number 52
 
0.1%
Lowercase Letter 39
 
< 0.1%
Connector Punctuation 2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 15576
19.7%
R 8428
 
10.6%
I 4680
 
5.9%
N 4643
 
5.9%
H 4600
 
5.8%
U 4485
 
5.7%
L 3870
 
4.9%
T 3681
 
4.7%
O 3225
 
4.1%
D 3095
 
3.9%
Other values (15) 22862
28.9%
Other Punctuation
ValueCountFrequency (%)
. 1007
98.7%
/ 11
 
1.1%
& 2
 
0.2%
Lowercase Letter
ValueCountFrequency (%)
a 13
33.3%
n 13
33.3%
d 13
33.3%
Decimal Number
ValueCountFrequency (%)
2 26
50.0%
4 26
50.0%
Space Separator
ValueCountFrequency (%)
1967
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 84
100.0%
Open Punctuation
ValueCountFrequency (%)
( 56
100.0%
Close Punctuation
ValueCountFrequency (%)
) 56
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 79184
96.1%
Common 3237
 
3.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 15576
19.7%
R 8428
 
10.6%
I 4680
 
5.9%
N 4643
 
5.9%
H 4600
 
5.8%
U 4485
 
5.7%
L 3870
 
4.9%
T 3681
 
4.6%
O 3225
 
4.1%
D 3095
 
3.9%
Other values (18) 22901
28.9%
Common
ValueCountFrequency (%)
1967
60.8%
. 1007
31.1%
- 84
 
2.6%
( 56
 
1.7%
) 56
 
1.7%
2 26
 
0.8%
4 26
 
0.8%
/ 11
 
0.3%
_ 2
 
0.1%
& 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82421
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 15576
18.9%
R 8428
 
10.2%
I 4680
 
5.7%
N 4643
 
5.6%
H 4600
 
5.6%
U 4485
 
5.4%
L 3870
 
4.7%
T 3681
 
4.5%
O 3225
 
3.9%
D 3095
 
3.8%
Other values (28) 26138
31.7%

Year
Real number (ℝ)

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2007.1625
Minimum2001
Maximum2013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:16.369907image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum2001
5-th percentile2001
Q12004
median2007
Q32010
95-th percentile2013
Maximum2013
Range12
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.7552323
Coefficient of variation (CV)0.0018709159
Kurtosis-1.2201411
Mean2007.1625
Median Absolute Deviation (MAD)3
Skewness-0.05209234
Sum19746465
Variance14.10177
MonotonicityIncreasing
2023-09-14T23:01:16.891906image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
2013 823
 
8.4%
2012 811
 
8.2%
2011 791
 
8.0%
2010 779
 
7.9%
2009 766
 
7.8%
2008 761
 
7.7%
2007 743
 
7.6%
2006 740
 
7.5%
2005 734
 
7.5%
2004 729
 
7.4%
Other values (3) 2161
22.0%
ValueCountFrequency (%)
2001 715
7.3%
2002 719
7.3%
2003 727
7.4%
2004 729
7.4%
2005 734
7.5%
2006 740
7.5%
2007 743
7.6%
2008 761
7.7%
2009 766
7.8%
2010 779
7.9%
ValueCountFrequency (%)
2013 823
8.4%
2012 811
8.2%
2011 791
8.0%
2010 779
7.9%
2009 766
7.8%
2008 761
7.7%
2007 743
7.6%
2006 740
7.5%
2005 734
7.5%
2004 729
7.4%

Murder
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct125
Distinct (%)1.4%
Missing834
Missing (%)8.5%
Infinite0
Infinite (%)0.0%
Mean3.7829853
Minimum0
Maximum528
Zeros4491
Zeros (%)45.6%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:17.495892image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile11
Maximum528
Range528
Interquartile range (IQR)3

Descriptive statistics

Standard deviation19.33503
Coefficient of variation (CV)5.1110507
Kurtosis329.24416
Mean3.7829853
Median Absolute Deviation (MAD)1
Skewness16.281745
Sum34062
Variance373.84338
MonotonicityNot monotonic
2023-09-14T23:01:18.177908image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4491
45.6%
1 1160
 
11.8%
2 803
 
8.2%
3 614
 
6.2%
4 423
 
4.3%
5 334
 
3.4%
6 239
 
2.4%
7 172
 
1.7%
8 139
 
1.4%
9 111
 
1.1%
Other values (115) 518
 
5.3%
(Missing) 834
 
8.5%
ValueCountFrequency (%)
0 4491
45.6%
1 1160
 
11.8%
2 803
 
8.2%
3 614
 
6.2%
4 423
 
4.3%
5 334
 
3.4%
6 239
 
2.4%
7 172
 
1.7%
8 139
 
1.4%
9 111
 
1.1%
ValueCountFrequency (%)
528 1
< 0.1%
489 1
< 0.1%
463 1
< 0.1%
458 1
< 0.1%
426 1
< 0.1%
424 1
< 0.1%
397 1
< 0.1%
390 1
< 0.1%
376 1
< 0.1%
372 1
< 0.1%

Rape
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct230
Distinct (%)2.3%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean14.044673
Minimum0
Maximum2112
Zeros3927
Zeros (%)39.9%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:18.918142image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q311
95-th percentile41
Maximum2112
Range2112
Interquartile range (IQR)11

Descriptive statistics

Standard deviation65.945096
Coefficient of variation (CV)4.6953814
Kurtosis281.15641
Mean14.044673
Median Absolute Deviation (MAD)2
Skewness14.407057
Sum138017
Variance4348.7557
MonotonicityNot monotonic
2023-09-14T23:01:19.574154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3927
39.9%
1 605
 
6.1%
2 479
 
4.9%
3 470
 
4.8%
4 385
 
3.9%
5 311
 
3.2%
6 273
 
2.8%
7 254
 
2.6%
8 245
 
2.5%
9 223
 
2.3%
Other values (220) 2655
27.0%
ValueCountFrequency (%)
0 3927
39.9%
1 605
 
6.1%
2 479
 
4.9%
3 470
 
4.8%
4 385
 
3.9%
5 311
 
3.2%
6 273
 
2.8%
7 254
 
2.6%
8 245
 
2.5%
9 223
 
2.3%
ValueCountFrequency (%)
2112 1
< 0.1%
1632 1
< 0.1%
1546 1
< 0.1%
1381 1
< 0.1%
1262 1
< 0.1%
1182 1
< 0.1%
1088 1
< 0.1%
1071 1
< 0.1%
1043 1
< 0.1%
1040 1
< 0.1%

Kidnapping and Abduction
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct327
Distinct (%)3.3%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean23.357077
Minimum0
Maximum6002
Zeros4250
Zeros (%)43.2%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:20.239155image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q312
95-th percentile68
Maximum6002
Range6002
Interquartile range (IQR)12

Descriptive statistics

Standard deviation150.40414
Coefficient of variation (CV)6.4393391
Kurtosis692.36693
Mean23.357077
Median Absolute Deviation (MAD)2
Skewness22.691531
Sum229530
Variance22621.406
MonotonicityNot monotonic
2023-09-14T23:01:20.910156image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 4250
43.2%
1 587
 
6.0%
2 421
 
4.3%
3 369
 
3.8%
4 331
 
3.4%
5 261
 
2.7%
6 250
 
2.5%
7 209
 
2.1%
8 185
 
1.9%
10 169
 
1.7%
Other values (317) 2795
28.4%
ValueCountFrequency (%)
0 4250
43.2%
1 587
 
6.0%
2 421
 
4.3%
3 369
 
3.8%
4 331
 
3.4%
5 261
 
2.7%
6 250
 
2.5%
7 209
 
2.1%
8 185
 
1.9%
9 160
 
1.6%
ValueCountFrequency (%)
6002 1
< 0.1%
5809 1
< 0.1%
4239 1
< 0.1%
3739 1
< 0.1%
3686 1
< 0.1%
3528 1
< 0.1%
2982 1
< 0.1%
2546 1
< 0.1%
2262 1
< 0.1%
2248 1
< 0.1%

Foeticide
Real number (ℝ)

ZEROS 

Distinct33
Distinct (%)0.3%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.29652997
Minimum0
Maximum79
Zeros9014
Zeros (%)91.6%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:21.565156image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum79
Range79
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.9535599
Coefficient of variation (CV)6.5880692
Kurtosis476.99875
Mean0.29652997
Median Absolute Deviation (MAD)0
Skewness17.32014
Sum2914
Variance3.8163965
MonotonicityNot monotonic
2023-09-14T23:01:22.176155image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 9014
91.6%
1 402
 
4.1%
2 138
 
1.4%
3 55
 
0.6%
4 50
 
0.5%
5 40
 
0.4%
6 20
 
0.2%
7 19
 
0.2%
10 15
 
0.2%
9 11
 
0.1%
Other values (23) 63
 
0.6%
(Missing) 11
 
0.1%
ValueCountFrequency (%)
0 9014
91.6%
1 402
 
4.1%
2 138
 
1.4%
3 55
 
0.6%
4 50
 
0.5%
5 40
 
0.4%
6 20
 
0.2%
7 19
 
0.2%
8 7
 
0.1%
9 11
 
0.1%
ValueCountFrequency (%)
79 1
< 0.1%
64 1
< 0.1%
39 1
< 0.1%
38 1
< 0.1%
37 1
< 0.1%
35 1
< 0.1%
34 1
< 0.1%
28 1
< 0.1%
25 2
< 0.1%
24 1
< 0.1%

Abetment of suicide
Real number (ℝ)

SKEWED  ZEROS 

Distinct24
Distinct (%)0.2%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.1572199
Minimum0
Maximum95
Zeros9319
Zeros (%)94.7%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:22.795154image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum95
Range95
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.6285445
Coefficient of variation (CV)10.358386
Kurtosis1656.588
Mean0.1572199
Median Absolute Deviation (MAD)0
Skewness34.858897
Sum1545
Variance2.6521571
MonotonicityNot monotonic
2023-09-14T23:01:23.391180image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0 9319
94.7%
1 285
 
2.9%
2 85
 
0.9%
3 39
 
0.4%
4 26
 
0.3%
5 13
 
0.1%
6 12
 
0.1%
7 11
 
0.1%
8 7
 
0.1%
9 5
 
0.1%
Other values (14) 25
 
0.3%
(Missing) 11
 
0.1%
ValueCountFrequency (%)
0 9319
94.7%
1 285
 
2.9%
2 85
 
0.9%
3 39
 
0.4%
4 26
 
0.3%
5 13
 
0.1%
6 12
 
0.1%
7 11
 
0.1%
8 7
 
0.1%
9 5
 
0.1%
ValueCountFrequency (%)
95 1
< 0.1%
67 1
< 0.1%
57 1
< 0.1%
36 1
< 0.1%
26 1
< 0.1%
25 1
< 0.1%
21 1
< 0.1%
19 1
< 0.1%
16 2
< 0.1%
14 1
< 0.1%

Exposure and abandonment
Real number (ℝ)

ZEROS 

Distinct97
Distinct (%)1.0%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2.1208914
Minimum0
Maximum321
Zeros7673
Zeros (%)78.0%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:24.009180image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile9
Maximum321
Range321
Interquartile range (IQR)0

Descriptive statistics

Standard deviation12.827086
Coefficient of variation (CV)6.0479691
Kurtosis280.55187
Mean2.1208914
Median Absolute Deviation (MAD)0
Skewness15.186055
Sum20842
Variance164.53413
MonotonicityNot monotonic
2023-09-14T23:01:24.655191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 7673
78.0%
1 453
 
4.6%
2 308
 
3.1%
3 203
 
2.1%
4 201
 
2.0%
5 146
 
1.5%
6 125
 
1.3%
7 100
 
1.0%
8 94
 
1.0%
9 89
 
0.9%
Other values (87) 435
 
4.4%
ValueCountFrequency (%)
0 7673
78.0%
1 453
 
4.6%
2 308
 
3.1%
3 203
 
2.1%
4 201
 
2.0%
5 146
 
1.5%
6 125
 
1.3%
7 100
 
1.0%
8 94
 
1.0%
9 89
 
0.9%
ValueCountFrequency (%)
321 1
< 0.1%
297 1
< 0.1%
293 1
< 0.1%
282 1
< 0.1%
281 1
< 0.1%
274 2
< 0.1%
259 1
< 0.1%
255 1
< 0.1%
249 1
< 0.1%
226 1
< 0.1%

Procuration of minor girls
Real number (ℝ)

SKEWED  ZEROS 

Distinct76
Distinct (%)0.8%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean1.0792714
Minimum0
Maximum486
Zeros9013
Zeros (%)91.6%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:25.337190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum486
Range486
Interquartile range (IQR)0

Descriptive statistics

Standard deviation10.004148
Coefficient of variation (CV)9.269353
Kurtosis919.92209
Mean1.0792714
Median Absolute Deviation (MAD)0
Skewness25.54404
Sum10606
Variance100.08297
MonotonicityNot monotonic
2023-09-14T23:01:26.031190image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 9013
91.6%
1 203
 
2.1%
2 101
 
1.0%
3 74
 
0.8%
4 49
 
0.5%
5 41
 
0.4%
7 34
 
0.3%
8 27
 
0.3%
6 26
 
0.3%
9 23
 
0.2%
Other values (66) 236
 
2.4%
ValueCountFrequency (%)
0 9013
91.6%
1 203
 
2.1%
2 101
 
1.0%
3 74
 
0.8%
4 49
 
0.5%
5 41
 
0.4%
6 26
 
0.3%
7 34
 
0.3%
8 27
 
0.3%
9 23
 
0.2%
ValueCountFrequency (%)
486 1
< 0.1%
369 1
< 0.1%
298 1
< 0.1%
210 1
< 0.1%
200 1
< 0.1%
193 1
< 0.1%
183 1
< 0.1%
152 1
< 0.1%
146 1
< 0.1%
142 2
< 0.1%

Buying of girls for prostitution
Real number (ℝ)

SKEWED  ZEROS 

Distinct21
Distinct (%)0.2%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.070825277
Minimum0
Maximum48
Zeros9705
Zeros (%)98.6%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:26.611192image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum48
Range48
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2009862
Coefficient of variation (CV)16.957027
Kurtosis749.20123
Mean0.070825277
Median Absolute Deviation (MAD)0
Skewness25.406938
Sum696
Variance1.4423678
MonotonicityNot monotonic
2023-09-14T23:01:27.219983image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0 9705
98.6%
1 60
 
0.6%
2 15
 
0.2%
3 11
 
0.1%
5 6
 
0.1%
9 5
 
0.1%
8 4
 
< 0.1%
31 2
 
< 0.1%
27 2
 
< 0.1%
29 2
 
< 0.1%
Other values (11) 15
 
0.2%
(Missing) 11
 
0.1%
ValueCountFrequency (%)
0 9705
98.6%
1 60
 
0.6%
2 15
 
0.2%
3 11
 
0.1%
4 2
 
< 0.1%
5 6
 
0.1%
6 2
 
< 0.1%
8 4
 
< 0.1%
9 5
 
0.1%
11 1
 
< 0.1%
ValueCountFrequency (%)
48 1
< 0.1%
45 1
< 0.1%
31 2
< 0.1%
29 2
< 0.1%
27 2
< 0.1%
25 1
< 0.1%
23 2
< 0.1%
22 1
< 0.1%
20 1
< 0.1%
19 1
< 0.1%

Selling of girls for prostitution
Real number (ℝ)

SKEWED  ZEROS 

Distinct37
Distinct (%)0.4%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.17685967
Minimum0
Maximum115
Zeros9545
Zeros (%)97.0%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:27.798966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum115
Range115
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.5758318
Coefficient of variation (CV)14.564268
Kurtosis1062.5853
Mean0.17685967
Median Absolute Deviation (MAD)0
Skewness29.18916
Sum1738
Variance6.6349092
MonotonicityNot monotonic
2023-09-14T23:01:28.408982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 9545
97.0%
1 134
 
1.4%
2 47
 
0.5%
3 19
 
0.2%
4 17
 
0.2%
6 10
 
0.1%
9 6
 
0.1%
10 5
 
0.1%
7 4
 
< 0.1%
13 4
 
< 0.1%
Other values (27) 36
 
0.4%
(Missing) 11
 
0.1%
ValueCountFrequency (%)
0 9545
97.0%
1 134
 
1.4%
2 47
 
0.5%
3 19
 
0.2%
4 17
 
0.2%
5 3
 
< 0.1%
6 10
 
0.1%
7 4
 
< 0.1%
8 1
 
< 0.1%
9 6
 
0.1%
ValueCountFrequency (%)
115 1
< 0.1%
114 1
< 0.1%
87 1
< 0.1%
69 1
< 0.1%
56 1
< 0.1%
55 1
< 0.1%
49 1
< 0.1%
44 1
< 0.1%
41 1
< 0.1%
40 1
< 0.1%

Prohibition of child marriage act
Real number (ℝ)

ZEROS 

Distinct31
Distinct (%)0.3%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean0.27312506
Minimum0
Maximum56
Zeros8857
Zeros (%)90.0%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:29.019988image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum56
Range56
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7277837
Coefficient of variation (CV)6.3259799
Kurtosis321.07997
Mean0.27312506
Median Absolute Deviation (MAD)0
Skewness15.304622
Sum2684
Variance2.9852363
MonotonicityNot monotonic
2023-09-14T23:01:29.557987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 8857
90.0%
1 593
 
6.0%
2 155
 
1.6%
3 66
 
0.7%
4 37
 
0.4%
5 22
 
0.2%
6 22
 
0.2%
8 9
 
0.1%
7 8
 
0.1%
11 6
 
0.1%
Other values (21) 52
 
0.5%
(Missing) 11
 
0.1%
ValueCountFrequency (%)
0 8857
90.0%
1 593
 
6.0%
2 155
 
1.6%
3 66
 
0.7%
4 37
 
0.4%
5 22
 
0.2%
6 22
 
0.2%
7 8
 
0.1%
8 9
 
0.1%
9 5
 
0.1%
ValueCountFrequency (%)
56 1
 
< 0.1%
43 3
< 0.1%
38 1
 
< 0.1%
30 1
 
< 0.1%
29 2
< 0.1%
26 3
< 0.1%
25 2
< 0.1%
23 1
 
< 0.1%
22 1
 
< 0.1%
21 1
 
< 0.1%

Other Crimes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct277
Distinct (%)2.8%
Missing11
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean16.455378
Minimum0
Maximum3502
Zeros5883
Zeros (%)59.8%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:30.215966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q35
95-th percentile60
Maximum3502
Range3502
Interquartile range (IQR)5

Descriptive statistics

Standard deviation111.42982
Coefficient of variation (CV)6.7716355
Kurtosis439.87797
Mean16.455378
Median Absolute Deviation (MAD)0
Skewness19.072792
Sum161707
Variance12416.605
MonotonicityNot monotonic
2023-09-14T23:01:30.871966image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5883
59.8%
1 478
 
4.9%
2 372
 
3.8%
3 272
 
2.8%
4 215
 
2.2%
5 184
 
1.9%
6 165
 
1.7%
7 155
 
1.6%
9 103
 
1.0%
11 89
 
0.9%
Other values (267) 1911
 
19.4%
ValueCountFrequency (%)
0 5883
59.8%
1 478
 
4.9%
2 372
 
3.8%
3 272
 
2.8%
4 215
 
2.2%
5 184
 
1.9%
6 165
 
1.7%
7 155
 
1.6%
8 88
 
0.9%
9 103
 
1.0%
ValueCountFrequency (%)
3502 1
< 0.1%
3004 1
< 0.1%
2869 1
< 0.1%
2861 1
< 0.1%
2625 1
< 0.1%
2595 1
< 0.1%
2572 1
< 0.1%
2520 1
< 0.1%
2487 1
< 0.1%
2324 1
< 0.1%

Total
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct508
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.782781
Minimum0
Maximum9857
Zeros2692
Zeros (%)27.4%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:31.589983image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12
Q342
95-th percentile170
Maximum9857
Range9857
Interquartile range (IQR)42

Descriptive statistics

Standard deviation305.16641
Coefficient of variation (CV)4.9393441
Kurtosis304.60879
Mean61.782781
Median Absolute Deviation (MAD)12
Skewness15.02821
Sum607819
Variance93126.54
MonotonicityNot monotonic
2023-09-14T23:01:32.262964image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2692
27.4%
1 400
 
4.1%
2 288
 
2.9%
3 234
 
2.4%
4 215
 
2.2%
5 183
 
1.9%
6 181
 
1.8%
8 161
 
1.6%
7 158
 
1.6%
10 139
 
1.4%
Other values (498) 5187
52.7%
ValueCountFrequency (%)
0 2692
27.4%
1 400
 
4.1%
2 288
 
2.9%
3 234
 
2.4%
4 215
 
2.2%
5 183
 
1.9%
6 181
 
1.8%
7 158
 
1.6%
8 161
 
1.6%
9 123
 
1.3%
ValueCountFrequency (%)
9857 1
< 0.1%
8247 1
< 0.1%
7199 1
< 0.1%
6410 1
< 0.1%
6033 1
< 0.1%
5500 1
< 0.1%
5168 1
< 0.1%
4912 1
< 0.1%
4646 1
< 0.1%
4462 1
< 0.1%

Infanticid
Real number (ℝ)

MISSING  ZEROS 

Distinct11
Distinct (%)1.3%
Missing9015
Missing (%)91.6%
Infinite0
Infinite (%)0.0%
Mean0.19927096
Minimum0
Maximum15
Zeros760
Zeros (%)7.7%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:33.725967image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum15
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1113874
Coefficient of variation (CV)5.5772672
Kurtosis85.747678
Mean0.19927096
Median Absolute Deviation (MAD)0
Skewness8.619317
Sum164
Variance1.2351819
MonotonicityNot monotonic
2023-09-14T23:01:34.207986image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 760
 
7.7%
1 41
 
0.4%
2 7
 
0.1%
3 3
 
< 0.1%
8 3
 
< 0.1%
7 2
 
< 0.1%
10 2
 
< 0.1%
4 2
 
< 0.1%
15 1
 
< 0.1%
6 1
 
< 0.1%
(Missing) 9015
91.6%
ValueCountFrequency (%)
0 760
7.7%
1 41
 
0.4%
2 7
 
0.1%
3 3
 
< 0.1%
4 2
 
< 0.1%
6 1
 
< 0.1%
7 2
 
< 0.1%
8 3
 
< 0.1%
10 2
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
15 1
 
< 0.1%
13 1
 
< 0.1%
10 2
 
< 0.1%
8 3
 
< 0.1%
7 2
 
< 0.1%
6 1
 
< 0.1%
4 2
 
< 0.1%
3 3
 
< 0.1%
2 7
 
0.1%
1 41
0.4%

Other murder
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct34
Distinct (%)4.1%
Missing9015
Missing (%)91.6%
Infinite0
Infinite (%)0.0%
Mean4.0267315
Minimum0
Maximum482
Zeros360
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size153.7 KiB
2023-09-14T23:01:34.780965image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile11
Maximum482
Range482
Interquartile range (IQR)3

Descriptive statistics

Standard deviation20.250181
Coefficient of variation (CV)5.0289376
Kurtosis389.34005
Mean4.0267315
Median Absolute Deviation (MAD)1
Skewness17.722221
Sum3314
Variance410.06984
MonotonicityNot monotonic
2023-09-14T23:01:35.394982image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0 360
 
3.7%
1 140
 
1.4%
2 79
 
0.8%
3 53
 
0.5%
4 50
 
0.5%
5 26
 
0.3%
6 23
 
0.2%
7 18
 
0.2%
8 11
 
0.1%
9 10
 
0.1%
Other values (24) 53
 
0.5%
(Missing) 9015
91.6%
ValueCountFrequency (%)
0 360
3.7%
1 140
 
1.4%
2 79
 
0.8%
3 53
 
0.5%
4 50
 
0.5%
5 26
 
0.3%
6 23
 
0.2%
7 18
 
0.2%
8 11
 
0.1%
9 10
 
0.1%
ValueCountFrequency (%)
482 1
< 0.1%
191 1
< 0.1%
114 1
< 0.1%
101 1
< 0.1%
87 1
< 0.1%
83 1
< 0.1%
77 1
< 0.1%
73 1
< 0.1%
68 1
< 0.1%
64 2
< 0.1%

Interactions

2023-09-14T23:00:53.862940image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:42.714337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:51.562100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:59.622083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:08.148100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:17.169210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:25.848227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:36.267104image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:47.199320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:55.882584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:06.561017image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:15.727903image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:24.428902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:33.615952image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:42.273380image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:54.489936image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:43.391055image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:52.097092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:00.166101image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:08.979107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:17.743224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:26.385209image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:36.867255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:47.837584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:56.442591image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:07.133032image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:16.288905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:25.023893image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:34.251520image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:42.944041image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:54.905923image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:43.923102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:52.619100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:00.723100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:09.509099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:18.301211image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:26.920224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:37.494242image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:48.425589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:56.990602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:07.701018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:16.826887image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:25.593906image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:34.862523image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:45.965638image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:55.456939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:44.421101image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:53.232087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:01.211084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:10.029114image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:18.828217image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:27.420226image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:38.032256image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:48.947616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:57.517612image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:08.250037image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:17.369904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:26.129902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:35.371510image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:46.518626image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:56.049937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:44.989098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:53.766086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:01.767099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:10.630110image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:19.418209image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:27.981209image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:38.654242image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:49.539606image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:58.102601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:08.876038image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:17.969911image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:26.732904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:35.944509image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:47.138628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:56.673927image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:45.935083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:54.316102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:02.346091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:11.250100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:20.030209image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:29.229225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:39.277259image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:50.151599image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:58.720585image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:09.547034image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:18.593906image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:27.361888image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:36.530519image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:47.771643image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:57.215938image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:46.457099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:54.854084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:02.844085image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:11.790084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:20.564222image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:29.802225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:39.867255image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:50.684608image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:59.253589image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:10.106045image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:19.181906image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:27.925905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:37.046518image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:48.343620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:57.774939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:47.025100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:55.414105image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:03.406099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:12.379086image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:21.153227image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:30.477216image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:42.279686image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:51.266586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:59.842604image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:10.760029image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:19.773892image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:28.524904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:37.610504image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:48.944643image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:58.344939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:47.571100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:56.001102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:03.936101image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:12.951107image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:21.717225image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:31.024210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:42.882690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:51.822596image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:00.436602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:11.475040image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:20.339912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:29.137902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:38.158502image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:49.567623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:59.018937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:48.120099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:56.538100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:04.846089image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:13.537098image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:22.291224image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:31.564210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:43.514688image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:52.385602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:00.982603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:12.047033image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:20.897905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:29.728904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:38.705530image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:50.259628image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:59.641939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:48.695099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:57.101099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:05.397103image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:14.135100image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:22.885212image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:32.136229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:44.110712image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:52.964601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:01.555601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:12.635024image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:21.482904image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:30.338892image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:39.283519image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:50.900939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:01:00.335677image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:49.245099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:57.618084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:05.926101image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:14.765069image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:23.472229image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:32.723211image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:44.682729image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:53.542592image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:02.118586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:13.275902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:22.045893image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:30.965495image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:39.845519image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:51.493935image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:01:00.936663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:49.816092image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:58.161083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:06.480102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:15.372060image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:24.067226image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:33.560320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:45.318714image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:54.143586image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:02.722601image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:13.910905image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:22.659903image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:31.654701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:40.473700image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:52.119923image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:01:01.497674image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:50.361083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:58.723099image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:07.004101image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:15.916068image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:24.617218image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:34.473404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:45.889735image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:54.683602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:05.252019image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:14.471902image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:23.193892image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:32.215715image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:41.023697image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:52.687944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:01:02.080667image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:50.986084image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:58:59.161087image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:07.584094image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:16.538215image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:25.238210image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:35.664101image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:46.627308image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T22:59:55.300600image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:05.935018image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:15.112894image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:23.824894image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:33.012953image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:41.721390image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-09-14T23:00:53.293937image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-09-14T23:01:35.999945image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
YearMurderRapeKidnapping and AbductionFoeticideAbetment of suicideExposure and abandonmentProcuration of minor girlsBuying of girls for prostitutionSelling of girls for prostitutionProhibition of child marriage actOther CrimesTotalInfanticidOther murder
Year1.0000.1020.2500.2920.0630.0870.0130.0370.0070.0470.0460.1230.258NaNNaN
Murder0.1021.0000.6770.6530.2430.2310.3320.2200.1160.1150.2040.5120.757NaNNaN
Rape0.2500.6771.0000.7490.2960.2860.3830.2330.1290.1440.2180.6080.8870.2520.591
Kidnapping and Abduction0.2920.6530.7491.0000.2690.2430.3810.2110.1470.1740.2180.5100.8670.2520.625
Foeticide0.0630.2430.2960.2691.0000.2430.2680.1540.1370.1660.1780.2410.3040.2140.279
Abetment of suicide0.0870.2310.2860.2430.2431.0000.2070.1870.1440.1740.1980.2830.2870.2340.240
Exposure and abandonment0.0130.3320.3830.3810.2680.2071.0000.1740.1190.1240.2410.3210.4510.1790.278
Procuration of minor girls0.0370.2200.2330.2110.1540.1870.1741.0000.2250.3310.2150.1950.2840.1110.199
Buying of girls for prostitution0.0070.1160.1290.1470.1370.1440.1190.2251.0000.3300.1060.1250.1500.1160.111
Selling of girls for prostitution0.0470.1150.1440.1740.1660.1740.1240.3310.3301.0000.1740.1300.1960.1100.211
Prohibition of child marriage act0.0460.2040.2180.2180.1780.1980.2410.2150.1060.1741.0000.2100.2710.1600.287
Other Crimes0.1230.5120.6080.5100.2410.2830.3210.1950.1250.1300.2101.0000.7040.2420.479
Total0.2580.7570.8870.8670.3040.2870.4510.2840.1500.1960.2710.7041.0000.2770.692
InfanticidNaNNaN0.2520.2520.2140.2340.1790.1110.1160.1100.1600.2420.2771.0000.247
Other murderNaNNaN0.5910.6250.2790.2400.2780.1990.1110.2110.2870.4790.6920.2471.000

Missing values

2023-09-14T23:01:03.247082image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-09-14T23:01:04.856077image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-09-14T23:01:07.377977image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

STATE/UTDISTRICTYearMurderRapeKidnapping and AbductionFoeticideAbetment of suicideExposure and abandonmentProcuration of minor girlsBuying of girls for prostitutionSelling of girls for prostitutionProhibition of child marriage actOther CrimesTotalInfanticidOther murder
0ANDHRA PRADESHADILABAD20010.00.00.00.00.00.00.00.00.00.00.00NaNNaN
1ANDHRA PRADESHANANTAPUR200119.012.029.00.06.00.00.00.00.00.00.066NaNNaN
2ANDHRA PRADESHCHITTOOR20010.00.00.00.00.00.00.00.00.00.00.00NaNNaN
3ANDHRA PRADESHCUDDAPAH20010.00.00.00.00.00.00.00.00.00.00.00NaNNaN
4ANDHRA PRADESHEAST GODAVARI20010.00.00.00.00.00.00.00.00.00.00.00NaNNaN
5ANDHRA PRADESHGUNTAKAL RLY.20010.00.00.00.00.00.00.00.00.00.00.00NaNNaN
6ANDHRA PRADESHGUNTUR20010.00.00.00.00.00.00.00.00.00.00.00NaNNaN
7ANDHRA PRADESHHYDERABAD CITY20012.00.00.00.00.019.02.00.00.02.00.025NaNNaN
8ANDHRA PRADESHKARIMNAGAR20011.04.00.00.00.03.00.00.00.00.01.09NaNNaN
9ANDHRA PRADESHKHAMMAM20010.00.00.00.00.00.00.00.00.00.00.00NaNNaN
STATE/UTDISTRICTYearMurderRapeKidnapping and AbductionFoeticideAbetment of suicideExposure and abandonmentProcuration of minor girlsBuying of girls for prostitutionSelling of girls for prostitutionProhibition of child marriage actOther CrimesTotalInfanticidOther murder
813Delhi UTSOUTH-EAST2013NaN120.0655.01.00.02.00.00.00.00.025.08080.05.0
814Delhi UTSOUTH-WEST2013NaN94.0503.01.00.03.00.00.00.01.086.06901.01.0
815Delhi UTSTF2013NaN0.00.00.00.00.00.00.00.00.00.000.00.0
816Delhi UTWEST2013NaN92.0671.00.01.03.00.00.00.00.0150.09230.06.0
817Delhi UTTOTAL2013NaN757.05809.03.01.056.00.00.00.01.0537.071992.033.0
818LakshadweepLAKSHADWEEP2013NaN0.00.00.00.00.00.00.00.00.00.000.00.0
819LakshadweepTOTAL2013NaN0.00.00.00.00.00.00.00.00.00.000.00.0
820PuducherryKARAIKAL2013NaN4.00.00.00.00.00.00.00.00.00.040.00.0
821PuducherryPUDUCHERRY2013NaN5.034.00.00.01.00.00.00.01.02.0430.00.0
822PuducherryTOTAL2013NaN9.034.00.00.01.00.00.00.01.02.0470.00.0

Duplicate rows

Most frequently occurring

STATE/UTDISTRICTYearMurderRapeKidnapping and AbductionFoeticideAbetment of suicideExposure and abandonmentProcuration of minor girlsBuying of girls for prostitutionSelling of girls for prostitutionProhibition of child marriage actOther CrimesTotalInfanticidOther murder# duplicates
0NAGALANDTOTAL20050.00.00.00.00.00.00.00.00.00.00.00NaNNaN2